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Topic: Transductive inference for text classification using SVMs
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Greg Hamerly  4
04-16-2001 11:06 AM ET (US)
First, the TSVM algorithm seems to me like a sort of EM for SVMs. Better yet, it seems even more like K-means because there is no partial assignment, only hard assignment, of test documents to the positive/negative classes. If this is the case, I think they should have used common terminology to describe this, rather than the term "transductive", which I don't think they defined well.

Second, they report average P/R breakeven numbers. They should have also reported the standard deviations for each of these numbers, to allow the reader to see if the averages are significantly different. Also, they say that the P/R breakeven point is a standard metric, but I would have appreciated the exact equation for computing that number.

I have general other gripes about this paper's over-use of mathematical symbols and complexity, I feel it could have been simplified.
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